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Claussen, E.R.* ; Renfrew, P.D.* ; Müller, C.L. ; Drew, K.*

Scaffold Matcher: A CMA-ES based algorithm for identifying hotspot aligned peptidomimetic scaffolds.

Proteins 92, 343-355 (2024)
Postprint DOI PMC
Open Access Hybrid
Creative Commons Lizenzvertrag
The design of protein interaction inhibitors is a promising approach to address aberrant protein interactions that cause disease. One strategy in designing inhibitors is to use peptidomimetic scaffolds that mimic the natural interaction interface. A central challenge in using peptidomimetics as protein interaction inhibitors, however, is determining how best the molecular scaffold aligns to the residues of the interface it is attempting to mimic. Here we present the Scaffold Matcher algorithm that aligns a given molecular scaffold onto hotspot residues from a protein interaction interface. To optimize the degrees of freedom of the molecular scaffold we implement the covariance matrix adaptation evolution strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm in Rosetta. To evaluate the performance of the CMA-ES, we used 26 peptides from the FlexPepDock Benchmark and compared with three other algorithms in Rosetta, specifically, Rosetta's default minimizer, a Monte Carlo protocol of small backbone perturbations, and a Genetic algorithm. We test the algorithms' performance on their ability to align a molecular scaffold to a series of hotspot residues (i.e., constraints) along native peptides. Of the 4 methods, CMA-ES was able to find the lowest energy conformation for all 26 benchmark peptides. Additionally, as a proof of concept, we apply the Scaffold Match algorithm with CMA-ES to align a peptidomimetic oligooxopiperazine scaffold to the hotspot residues of the substrate of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our implementation of CMA-ES into Rosetta allows for an alternative optimization method to be used on macromolecular modeling problems with rough energy landscapes. Finally, our Scaffold Matcher algorithm allows for the identification of initial conformations of interaction inhibitors that can be further designed and optimized as high-affinity reagents.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Cma-es ; Rosetta ; Covariance Matrix Adaptation Evolution Strategy ; Derivative-free Optimization ; Hotspot Residues ; Peptidomimetic ; Scaffold Matcher; Protein-protein Interactions; Computational Design; Optimization; Prediction; Inhibitors; Peptides; Binding
Sprache englisch
Veröffentlichungsjahr 2024
Prepublished im Jahr 2023
HGF-Berichtsjahr 2023
ISSN (print) / ISBN 0887-3585
e-ISSN 1097-0134
Zeitschrift Proteins: Structure, Function, and Bioinformatics
Quellenangaben Band: 92, Heft: 3, Seiten: 343-355 Artikelnummer: , Supplement: ,
Verlag Wiley
Verlagsort 111 River St, Hoboken 07030-5774, Nj Usa
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503800-001
Förderungen Rosetta Commons
National Institutes of Health
DOI 10.1002/prot.26619
WOS ID 001095610000001
Scopus ID 85174634930
PubMed ID 37874196
Erfassungsdatum 2023-11-28
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